Skip to main content

Constructing Data Graphs for Keyword Search

  • Conference paper
  • First Online:
Database and Expert Systems Applications (DEXA 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9828))

Included in the following conference series:

Abstract

Data graphs are convenient for supporting keyword search that takes into account available semantic structure and not just textual relevance. However, the problem of constructing data graphs that facilitate both efficiency and effectiveness of the underlying system has hardly been addressed. A conceptual model for this task is proposed. Principles for constructing good data graphs are explained. A transformation for generating data graphs from XML is developed.

This work was supported by the Israel Science Foundation (Grant No. 1632/12).

The full version of this paper appears in [9].

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    http://www.dbis.informatik.uni-goettingen.de/Mondial/.

References

  1. Achiezra, H., Golenberg, K., Kimelfeld, B., Sagiv, Y.: Exploratory keyword search on data graphs. In: SIGMOD Conference (2010)

    Google Scholar 

  2. Bao, Z., Ling, T.W., Chen, B., Lu, J.: Effective XML keyword search with relevance oriented ranking. In: ICDE (2009)

    Google Scholar 

  3. Bhalotia, G., Hulgeri, A., Nakhe, C., Chakrabarti, S., Sudarshan, S.: Keyword searching and browsing in databases using BANKS. In: ICDE (2002)

    Google Scholar 

  4. Coffman, J., Weaver, A.C.: An empirical performance evaluation of relational keyword search techniques. IEEE Trans. Knowl. Data Eng. 26(1), 30–42 (2014)

    Article  Google Scholar 

  5. Dalvi, B.B., Kshirsagar, M., Sudarshan, S.: Keyword search on external memory data graphs. PVLDB 1(1), 1189–1204 (2008)

    Google Scholar 

  6. Ding, B., Yu, J.X., Wang, S., Qin, L., Zhang, X., Lin, X.: Finding top-k min-cost connected trees in databases. In: ICDE (2007)

    Google Scholar 

  7. Golenberg, K., Kimelfeld, B., Sagiv, Y.: Keyword proximity search in complex data graphs. In: SIGMOD Conference (2008)

    Google Scholar 

  8. Golenberg, K., Kimelfeld, B., Sagiv, Y.: Optimizing and parallelizing ranked enumeration. PVLDB 4(11), 1028–1039 (2011)

    Google Scholar 

  9. Golenberg, K., Sagiv, Y.: Constructing data graphs for keyword search. arXiv: https://arxiv.org/abs/1605.07865 (2016)

  10. Golenberg, K., Sagiv, Y.: A practically efficient algorithm for generating answers to keyword search over data graphs. In: ICDT (2016)

    Google Scholar 

  11. Guo, L., Shao, F., Botev, C., Shanmugasundaram, J.: XRANK: ranked keyword search over XML documents. In: SIGMOD Conference (2003)

    Google Scholar 

  12. He, H., Wang, H., Yang, J., Yu, P.S.: BLINKS: ranked keyword searches on graphs. In: SIGMOD Conference (2007)

    Google Scholar 

  13. Hristidis, V., Papakonstantinou, Y., Balmin, A.: Keyword proximity search on XML graphs. In: ICDE (2003)

    Google Scholar 

  14. Kacholia, V., Pandit, S., Chakrabarti, S., Sudarshan, S., Desai, R., Karambelkar, H.: Bidirectional expansion for keyword search on graph databases. In: VLDB (2005)

    Google Scholar 

  15. Kasneci, G., Ramanath, M., Sozio, M., Suchanek, F.M., Weikum, G.: STAR: steiner-tree approximation in relationship graphs. In: ICDE (2009)

    Google Scholar 

  16. Li, G., Ooi, B.C., Feng, J., Wang, J., Zhou, L.: EASE: an effective 3-in-1 keyword search method for unstructured, semi-structured and structured data. In: SIGMOD Conference (2008)

    Google Scholar 

  17. Mass, Y., Sagiv, Y.: Virtual documents and answer priors in keyword search over data graphs. In: Proceedings of the Workshops of the EDBT/ICDT 2016 Joint Conference (2016)

    Google Scholar 

  18. Park, C., Lim, S.: Efficient processing of keyword queries over graph databases for finding effective answers. Inf. Process. Manage. 51(1), 42–57 (2015)

    Article  Google Scholar 

  19. Sagiv, Y.: A personal perspective on keyword search over data graphs. In: ICDT, pp. 21–32 (2013)

    Google Scholar 

  20. Xu, Y., Papakonstantinou, Y.: Efficient LCA based keyword search in XML data. In: EDBT (2008)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Konstantin Golenberg .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Golenberg, K., Sagiv, Y. (2016). Constructing Data Graphs for Keyword Search. In: Hartmann, S., Ma, H. (eds) Database and Expert Systems Applications. DEXA 2016. Lecture Notes in Computer Science(), vol 9828. Springer, Cham. https://doi.org/10.1007/978-3-319-44406-2_33

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-44406-2_33

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-44405-5

  • Online ISBN: 978-3-319-44406-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics